2 March 2017

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Overview

What does the Kalman filter do?

Kalman filtering, also known as linear quadratic estimation (LQE), is an algorithm that uses a series of measurements observed over time, containing statistical noise and other inaccuracies, and produces estimates of unknown variables that tend to be more accurate than those based on a single measurement alone, by using Bayesian inference and estimating a joint probability distribution over the variables for each timeframe. The filter is named after Rudolf E. Kálmán, one of the primary developers of its theory.

Source: WIKIPEDIA

Basic concept

Kalman process chart

Variable $ Functions

  • Original error estimate
  • Error in estimate
  • Calculate Kalman gain
  • Calculate current estimate
  • Previous estimate
  • Error in data (measurement)
  • Calculate new error in estimate
  • Updates estimate

Multiple variables

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